Faktora.ai Docs
  • Introduction
  • The Rise of DefAI: Why AI is the Next Evolution of DeFi
  • Problem & Solution
    • Agents Managing Their Own Wallets
    • Multi-Agent Orchestration
    • Web3 Fragmentation
    • Code Duplication & API Complexity
  • AI Agents as On-Chain Executors (No More Manual Trading, Just Talk to AI)
  • Architecture & Technical Overview
    • Multi-Agent Orchestration Explained (AI That Actually Talks to Itself)
    • Recursive Chat & AI Collaboration
    • AI Native On-Chain Communication
    • AI Learning Models & Optimization
    • Smart Execution Engine & Transaction Efficiency
    • Security, Compliance, and Risk Management
  • Tokenomics & Utility of $FAKT
  • Infrastructure & Developer Ecosystem
    • Building Custom AI Agents (Your AI, Your Rules)
    • AI Orchestration for dApps
    • AI-Driven Infrastructure Scaling & Performance Optimization
  • Community Links
    • Telegram
  • Twitter
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  • Faktora’s Smart Execution Engine
  • Dynamic Order Routing: Eliminating Slippage & Maximizing Execution Quality
  • On-Chain Transaction Intelligence: Avoiding MEV Exploits & Sandwich Attacks
  1. Architecture & Technical Overview

Smart Execution Engine & Transaction Efficiency

Transaction execution is the backbone of DeFi. Speed, cost, and precision determine profitability in trading, staking, and liquidity strategies. Poorly optimized execution leads to:

  • High gas costs – Unoptimized transactions waste ETH and make small trades unprofitable.

  • Slippage & price impact – Inefficient order routing causes traders to lose money on every swap.

  • MEV risks – Miners and validators front-run transactions, extracting value from users.

Faktora’s Smart Execution Engine

Faktora AI optimizes every aspect of execution, ensuring that trades, liquidity movements, and interactions with DeFi protocols are cost-efficient, rapid, and secure.

It achieves this through:

  1. AI-Optimized Gas Fee Reduction – Faktora minimizes gas usage via transaction batching and Layer 2 routing.

  2. Dynamic Order Routing – AI selects the most capital-efficient path across multiple DeFi protocols.

  3. On-Chain Transaction Intelligence – Faktora’s AI adjusts execution in real-time to avoid MEV threats, slippage, and sandwich attacks.

These components ensure that every transaction is optimized for cost-efficiency, speed, and security.


Dynamic Order Routing: Eliminating Slippage & Maximizing Execution Quality

The Problem with Standard DEX Trades

When users swap tokens on Uniswap or Curve, they often overpay due to slippage and liquidity fragmentation. Standard DEX routers:

  • Don’t always find the best price across all pools.

  • Aren’t optimized for large orders, leading to price impact.

  • Fail to predict liquidity changes, resulting in unexpected execution costs.

How Faktora’s AI Fixes This with Dynamic Order Routing

Faktora AI scans all available liquidity pools, AMMs, and aggregators before executing a trade.

  • Orders are split dynamically across multiple DEXs for best price execution.

  • AI pre-checks slippage risk, ensuring trades execute at expected prices.

  • Execution adapts to real-time liquidity shifts, preventing unnecessary losses.

Example: 📉 A trader wants to swap 500 ETH for USDC. 🚫 Uniswap v3 offers a 2.5% price impact. ✅ Faktora splits the trade across Uniswap, Curve, and Balancer, reducing slippage to 0.3%.

Execution Method
Slippage Cost

Uniswap v3 Only

2.5% (~12.5 ETH lost in price impact)

Faktora Dynamic Routing

0.3% (~1.5 ETH lost in price impact)

By optimizing order execution, Faktora ensures traders always get the best possible price.


On-Chain Transaction Intelligence: Avoiding MEV Exploits & Sandwich Attacks

Ethereum transactions are visible in the mempool before execution, meaning MEV bots can front-run, sandwich, or extract value from users.

1. How Faktora Prevents MEV & Frontrunning

Faktora’s AI detects potential MEV attacks before executing transactions by:

  • Pre-analyzing mempool data for signs of frontrunning activity.

  • Adjusting transaction timing to avoid being exploited.

  • Routing transactions through private relayers (e.g., Flashbots) to remain hidden.

Attack Type
Faktora Solution

Frontrunning

AI delays transaction execution to avoid pre-trade price manipulation.

Sandwich Attacks

AI adjusts slippage settings to avoid being targeted.

Backrunning

AI executes transactions through private mempools, preventing backrunning bots.

2. AI-Adaptive Trade Execution Timing

Unlike human traders, Faktora’s AI monitors optimal execution windows and adjusts trade timing dynamically:

  • Delays transactions when high MEV activity is detected.

  • Executes when block congestion is low, reducing slippage.

  • Uses Flashbots/private transactions to keep execution hidden from bots.

Example: 🛑 A user executes a $1M ETH → USDT trade. 🚨 MEV bots detect it and attempt a sandwich attack. ✅ Faktora’s AI detects the threat, reroutes execution through a private relayer, and blocks the attack.

This protects users from losing capital to unfair MEV extractions, making DeFi execution safer.


Faktora’s AI-powered Smart Execution Engine ensures that:

  • Trades execute at the lowest possible gas cost.

  • Liquidity is dynamically optimized, preventing slippage.

  • MEV threats are detected and neutralized before execution.

With transaction batching, order routing, and security-first execution strategies, Faktora offers the most capital-efficient way to trade and interact with DeFi.

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Last updated 2 months ago